Triple
T42196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe |
E833
|
entity |
| Predicate | continentOf |
P233
|
FINISHED |
| Object | European countries |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: European countries | Statement: [Europe, continentOf, European countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continentOf Context triple: [Europe, continentOf, European countries]
-
A.
continent
chosen
Indicates that one entity is a continent on which the other entity is geographically located or to which it belongs.
-
B.
continentOfCitizenship
Indicates the continent on which a person’s country of citizenship is located.
-
C.
countryAtTheTime
Indicates that an entity is associated with a specific country as it existed at a particular point in time.
-
D.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
-
E.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24db9527c8190816b6b25c88cb2f4 |
completed | Feb. 28, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69a24ab8a8908190beec6da6694dd4c9 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.